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    "BERT的性能强大，唯一的问题是其尺寸   \n",
    "- BERT-base 包含 110M 参数，BERT-large 包含 340M 参数，也因此很难将其部署到很多内存受限的环境中，如手机或嵌入式设备   \n",
    "\n",
    "也导致训练和推理非常耗时  \n",
    "\n",
    "\n",
    "优化神经网络：\n",
    "- 架构提升：如更改为更快模型架构，RNN替换成Transformer，更聪明的优化技术\n",
    "- 模型压缩：减枝等\n",
    "- 模型蒸馏：训练更小的模型，能够复现原始模型\n",
    "\n",
    "\n",
    "架构和优化：\n",
    "- 大规模的分布式训练\n",
    "- layerwise adaptive large batch optimization technique ： LAMB "
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